{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Temporal Convolutional Network\n",
    "In this notebook, we show an example of how TCNs can be used with darts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# fix python path if working locally\n",
    "from utils import fix_pythonpath_if_working_locally\n",
    "\n",
    "fix_pythonpath_if_working_locally()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from darts import TimeSeries\n",
    "from darts.models import TCNModel, RNNModel\n",
    "from darts.dataprocessing.transformers import Scaler\n",
    "from darts.utils.timeseries_generation import datetime_attribute_timeseries\n",
    "from darts.metrics import mape, r2_score\n",
    "from darts.utils.missing_values import fill_missing_values\n",
    "from darts.datasets import AirPassengersDataset, SunspotsDataset, EnergyDataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Air passengers dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read data:\n",
    "ts = AirPassengersDataset().load()\n",
    "scaler = Scaler()\n",
    "ts = scaler.fit_transform(\n",
    "    ts\n",
    ")  # scale the whole time series not caring about train/val split...\n",
    "\n",
    "# We'll use the month as a covariate\n",
    "month_series = datetime_attribute_timeseries(ts, attribute=\"month\", one_hot=True)\n",
    "scaler_month = Scaler()\n",
    "month_series = scaler_month.fit_transform(month_series)\n",
    "\n",
    "# Create training and validation sets:\n",
    "train, val = ts.split_after(pd.Timestamp(\"19580801\"))\n",
    "train_month, val_month = month_series.split_after(pd.Timestamp(\"19580801\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following cell, we will build a `TCNModel`. Later, when we train it, the model will initiate its internal input width to 2, as we have one dimension for the time series and another dimension for the covariate month time series (this will be transparent to us, though).\n",
    "Additionally, since we later want to simulate a historic forecast 6 months into the future, we have to make sure the `output_chunk_length` parameter of our `TCNModel` instance has a value of at least 6. \n",
    "\n",
    "If we don't specify the `num_layers` parameter, it will be chosen automatically to be the minimum number to ensure full history coverage for every entry in the output, i.e. every output will be dependent on the whole input."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_air = TCNModel(\n",
    "    input_chunk_length=13,\n",
    "    output_chunk_length=12,\n",
    "    n_epochs=500,\n",
    "    dropout=0.1,\n",
    "    dilation_base=2,\n",
    "    weight_norm=True,\n",
    "    kernel_size=5,\n",
    "    num_filters=3,\n",
    "    random_state=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2021-08-01 13:13:00,823] INFO | darts.models.torch_forecasting_model | Train dataset contains 92 samples.\n",
      "[2021-08-01 13:13:00,823] INFO | darts.models.torch_forecasting_model | Train dataset contains 92 samples.\n",
      "[2021-08-01 13:13:00,829] INFO | darts.models.tcn_model | Number of layers chosen: 2\n",
      "[2021-08-01 13:13:00,829] INFO | darts.models.tcn_model | Number of layers chosen: 2\n",
      "[2021-08-01 13:13:00,837] INFO | darts.models.torch_forecasting_model | Time series values are 64-bits; casting model to float64. If training is too slow you can try casting your data to 32-bits.\n",
      "[2021-08-01 13:13:00,837] INFO | darts.models.torch_forecasting_model | Time series values are 64-bits; casting model to float64. If training is too slow you can try casting your data to 32-bits.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0081c35ae05c4bc7bf48b5c2004b2899",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/500 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training loss: 0.0016, validation loss: 0.0037, best val loss: 0.0037\r"
     ]
    }
   ],
   "source": [
    "model_air.fit(\n",
    "    series=train,\n",
    "    past_covariates=train_month,\n",
    "    val_series=val,\n",
    "    val_past_covariates=val_month,\n",
    "    verbose=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's see what we get for a 6-months prediction:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "7180ae356295453e8ca7c33f4e90f4f3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/39 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "backtest = model_air.historical_forecasts(\n",
    "    series=ts,\n",
    "    past_covariates=month_series,\n",
    "    start=0.7,\n",
    "    forecast_horizon=6,\n",
    "    retrain=False,\n",
    "    verbose=True,\n",
    ")\n",
    "\n",
    "ts.plot(label=\"actual\")\n",
    "backtest.plot(label=\"backtest (H=6)\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Monthly sunspots\n",
    "Let's try using the `TCNModel` on a more complex and much bigger dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "series_sunspot = SunspotsDataset().load()\n",
    "scaler = Scaler()\n",
    "series_sp_transformed = scaler.fit_transform(series_sunspot)\n",
    "\n",
    "# series_sunspot = series_sunspot.add_datetime_attribute('month', True)\n",
    "train_sp_transformed, val_sp_transformed = series_sp_transformed.split_after(\n",
    "    pd.Timestamp(\"19401001\")\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_sun = TCNModel(\n",
    "    input_chunk_length=250,\n",
    "    output_chunk_length=36,\n",
    "    n_epochs=100,\n",
    "    dropout=0,\n",
    "    dilation_base=2,\n",
    "    weight_norm=True,\n",
    "    kernel_size=3,\n",
    "    num_filters=6,\n",
    "    nr_epochs_val_period=1,\n",
    "    random_state=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2021-08-01 13:13:39,307] INFO | darts.models.torch_forecasting_model | Train dataset contains 2017 samples.\n",
      "[2021-08-01 13:13:39,307] INFO | darts.models.torch_forecasting_model | Train dataset contains 2017 samples.\n",
      "[2021-08-01 13:13:39,310] INFO | darts.models.tcn_model | Number of layers chosen: 6\n",
      "[2021-08-01 13:13:39,310] INFO | darts.models.tcn_model | Number of layers chosen: 6\n",
      "[2021-08-01 13:13:39,314] INFO | darts.models.torch_forecasting_model | Time series values are 64-bits; casting model to float64. If training is too slow you can try casting your data to 32-bits.\n",
      "[2021-08-01 13:13:39,314] INFO | darts.models.torch_forecasting_model | Time series values are 64-bits; casting model to float64. If training is too slow you can try casting your data to 32-bits.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "0b66560e147b4ea087a6531de6a89819",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/100 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training loss: 0.0078, validation loss: 0.0346, best val loss: 0.0316\r"
     ]
    }
   ],
   "source": [
    "model_sun.fit(train_sp_transformed, val_series=val_sp_transformed, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "4e31958f83824aa4bf0cf9f645a46092",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/84 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "backtest_sp = model_sun.historical_forecasts(\n",
    "    series_sp_transformed,\n",
    "    start=0.7,\n",
    "    forecast_horizon=12,\n",
    "    stride=10,\n",
    "    retrain=False,\n",
    "    verbose=True,\n",
    ")\n",
    "\n",
    "series_sp_transformed[2000:].plot(label=\"actual\")\n",
    "backtest_sp.plot(label=\"backtest (H=12)\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Daily energy production"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df3 = EnergyDataset().load().pd_dataframe()\n",
    "df3_day_avg = (\n",
    "    df3.groupby(df3.index.astype(str).str.split(\" \").str[0]).mean().reset_index()\n",
    ")\n",
    "series_en = fill_missing_values(\n",
    "    TimeSeries.from_dataframe(\n",
    "        df3_day_avg, \"time\", [\"generation hydro run-of-river and poundage\"]\n",
    "    ),\n",
    "    \"auto\",\n",
    ")\n",
    "\n",
    "# scale\n",
    "scaler_en = Scaler()\n",
    "series_en_transformed = scaler_en.fit_transform(series_en)\n",
    "train_en_transformed, val_en_transformed = series_en_transformed.split_after(\n",
    "    pd.Timestamp(\"20170901\")\n",
    ")\n",
    "\n",
    "# add the day as a covariate\n",
    "day_series = datetime_attribute_timeseries(\n",
    "    series_en_transformed, attribute=\"day\", one_hot=True\n",
    ")\n",
    "scaler_day = Scaler()\n",
    "day_series = scaler_day.fit_transform(day_series)\n",
    "train_day, val_day = day_series.split_after(pd.Timestamp(\"20170901\"))\n",
    "\n",
    "series_en_transformed.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_en = TCNModel(\n",
    "    input_chunk_length=365,\n",
    "    output_chunk_length=7,\n",
    "    n_epochs=50,\n",
    "    dropout=0.2,\n",
    "    dilation_base=2,\n",
    "    weight_norm=True,\n",
    "    kernel_size=5,\n",
    "    num_filters=8,\n",
    "    nr_epochs_val_period=1,\n",
    "    random_state=0,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2021-08-01 13:17:10,560] INFO | darts.models.torch_forecasting_model | Train dataset contains 605 samples.\n",
      "[2021-08-01 13:17:10,560] INFO | darts.models.torch_forecasting_model | Train dataset contains 605 samples.\n",
      "[2021-08-01 13:17:10,563] INFO | darts.models.tcn_model | Number of layers chosen: 6\n",
      "[2021-08-01 13:17:10,563] INFO | darts.models.tcn_model | Number of layers chosen: 6\n",
      "[2021-08-01 13:17:10,570] INFO | darts.models.torch_forecasting_model | Time series values are 64-bits; casting model to float64. If training is too slow you can try casting your data to 32-bits.\n",
      "[2021-08-01 13:17:10,570] INFO | darts.models.torch_forecasting_model | Time series values are 64-bits; casting model to float64. If training is too slow you can try casting your data to 32-bits.\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a83d39117c5b4c58b072742a361ef12d",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/50 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training loss: 0.0083\r"
     ]
    }
   ],
   "source": [
    "model_en.fit(series=train_en_transformed, past_covariates=train_day, verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "6cc86cacffaf4dadbf0b7788438174d7",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/434 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "backtest_en = model_en.historical_forecasts(\n",
    "    series=series_en_transformed,\n",
    "    past_covariates=day_series,\n",
    "    start=0.7,\n",
    "    forecast_horizon=7,\n",
    "    stride=1,\n",
    "    retrain=False,\n",
    "    verbose=True,\n",
    ")\n",
    "\n",
    "plt.figure(figsize=(10, 6))\n",
    "series_en_transformed[800:].plot(label=\"actual\")\n",
    "backtest_en.plot(label=\"backtest (H=7)\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
